Fast & slow metrics: LTV & Loyalty

This is the first post of a series from Carlos Oliveira at Building Fast and Slow around how to think about your key metrics when building consumer products. In this first post, we look at one of the cornerstones of the economics of internet businesses. Customer lifetime value, or LTV, and its interplay with loyalty programs.

How to move the LTV needle

In general, any loyalty scheme is built around two key factors that brands use to incentivize customers in order to drive their Lifetime Value (LTV): one that’s financial, another that’s emotional.

On both accounts, what we’re doing is creating an incentive for our user that generates a net positive effect on Average Revenue Per User (ARPU), within a reasonable payback period given the SAC/CAC we incurred in (Subscriber Acquisition Cost/Customer Acquisition Cost), our Running Costs (and runway) and our Cost of Capital (WACC).

Usually, that is done by offering the customer a discounted offer on their current or proximal purchase / spend (with said discount in the form of price, promotion, convenience — such as shipping costs or upgrade options), which actually negatively impacts someone’s ARPU within a short time frame, while lowering the cost of their preference on a subsequent purchase (reacquisition costs, lowered price sensitivity), thus ending up positively impacting SAC/CAC and ARPU within what is called the payback period, through volume in incremental purchases.

If done effectively, it significantly raises barriers to exit, by virtue of a positive feedback loop that promotes an on-going relationship with the brand, where it becomes first to mind.

If not, the pitfalls of LTV kick-in and companies run out of runway before they make their CAC/LTV equation pay off — uber is a recent famous example where Venture Capital was used to drive growth with a clearly unsustainable CAC/LTV formula, to drive out competitors and establish a dominant market share in key geographies. One key thing to understand about LTV is that it is, by definition, very lagging. Because we’re waiting for a long enough time to come to completion in order to compare different cohorts of customers, we need many micro-moments of interaction with our brand touchpoints to occur, before decisions are made.

In order to measure their effectiveness, we want to look at incrementality. Typically those that are more sensitive to the effects of loyalty programs are already those more intent on purchasing frequently, typically leading to a self-selection effect emerging through the data, particularly when cohorts aren’t too big, making it hard for companies to understand the individual impact of their benefits and incentives.

For larger cohorts, companies can create holdout groups to control for these effects. The operating trade-off here is that you usually want to ensure your most loyal customers are immediately included in the program, getting full access to its benefits, and feeling that they’re valued, which makes things harder for those measuring it, as it may lead to an unreliable comparison with the holdout, which contains none of your most engaged customers. However, hard to measure isn’t impossible, and there is very strong reason to run cohort analysis, split testing whenever possible and even controlled experiments in order to successfully optimize loyalty programs.

Loyalty driving LTV

Let’s now look at a few well-known examples of brand loyalty incentives, aimed at increasing LTV through incremental ARPU. These include:

/Paid Bundled offerings

An interesting but hard to nail value proposition is a paid-for membership. Customers are required to pay for a subscription themselves (driving ARPU), which they will make up for in accrued value over time (potentially increasing Costs). The most famous is Amazon Prime, where customers pay a flat monthly/yearly fee to get free next-day delivery (which could cost up to $10+ per delivery). Additionally, Amazon has added a series of value-add services to the subscription (such as Video and Music), which incentivizes customers to continue using it for their commodity purchases, as well as to keep paying for continued access to their ancillary products.

• Amazon Prime
• B&N

/Spend-level offerings

//Tier-based

Tier-based programs are normally based on customers’ spend with the brand to gamify their relationship, using the promise of further rewards as a way to incentivize their continued relationship with the brand (+ARPU). The more customers have spent, the better (and more expensive for the brand, +Costs) the incentives would be, playing on both the economic function of the rewards, as well as the social status associated with them.

• Sephora (+ community)
• Farfetch

//Point-based

Points-based programs tend to use the same spend-based mechanism to reward customers, but they accrue points towards a flexible system within which a monetary function exists, to collect rewards towards their next purchase. This incentivizes customers to spend again within the points’ lifetime. Airlines are famous for rewarding frequent travelers with points, promoting them to not only stay loyal on their frequent business routes, but to also use them for personal travel. The high barrier to entry with points systems, also means that once customers are engaged and understand the point system fully, they become their biggest distribution channels.

• Nordstrom
• Airline Miles
• Nectar points

/Coupons & cash rewards based

Another type of loyalty scheme consists of rewarding customers directly with either cash back or coupons towards their next purchase. Whereas cashback ensures a customer uses a given card network or affiliate site (which pays customers out of the commission they get for driving the purchase), coupon-based loyalty schemes typically offer coupons towards a customers’ next purchase based on their own / their peers’ buying habits, diversifying customers’ basket of purchases and driving habitual purchasing behavior.

• Cashback schemes
• Branded credit cards
• Retailer loyalty cards

Customers make upfront investments in a brand in order to recoup them, over time, multiplied. Brands lower their margins for these segments in exchange for incrementality, ultimately driving lifetime value. By engaging with the program, there is also the expectation on the part of customers that they will come back, which is not always true — see projection bias — and that there’s a positive trade-off in choosing the seller over a competitor in a subsequent purchase. Rational or not, this guarantees that a larger share of wallet will be spent with the brand than would otherwise be the case.

Demand, once bought in, also tends to be less price elastic and more prone to making emotional decisions, thus more sensitive to coupon marketing, abandoned basket messaging, exclusive campaigns for commoditized / brand goods, sales seasons (particularly when combined with the possibility of creating exclusivity for loyal members).

Having programs such as these allows brands to create influence networks that treat power users as stars, growing their own proprietary distribution channels: If they become aspirational references for the masses, those who retain the greatest value out of these programs (the points addicts, the platinum card customers, the early adopters), then become a company’s greatest advocates, each bringing in many new customers and inspiring tens to thousands of less-than-committed followers. Not all of these will become power users themselves, but by virtue of believing that that is true, they’ll still prefer buying with the brand and chasing ever-fleeting rewards, which lowering acquisition and re-acquisition costs.

Finally, another lens through which to look at driving LTV through increased ARPU is the softer version of loyalty. Companies drive retention and loyalty through excellent levels of Customer Service, frictionless purchase experience (1-tap checkout), emotional attachment, or sunk data costs (such as your friends’ graph, a fully organized photo album or all your phone’s data fully backed up). The issue again is measuring the effectiveness of these practices beyond a principled approach to product and customer service, beyond the elusive but instinctive common sense.

As Jeff Bezos insists, however, “Your margin is my opportunity”, and driving excellent standards of customer experience has never been known to hurt a brand.